5 Reasons Your Data May be Dirty

Organizations analyze and rely on data that is inaccurate, incomplete, or cannot be reconciled. Dirty data results in poor investments and wasted resources.

Share this:

Why is Your Data Dirty?

We know the dangers of dirty water and the negative effects of chemicals and bacteria if water doesn’t go through a treatment and filtration process, but we don’t always think about the dangers of dirty data. In our latest eBook, The Clean Data Initiative, Pratish Kanani, our COO, compares how we treat data quality to water quality and highlights the parallels of the two situations. While we have organizations in place to keep the water we consume clean, many organizations don’t treat their data with the same care. They analyze and rely on data that is inaccurate, incomplete, duplicated, non-standard, or cannot be reconciled. Dirty data results in poor investments, wasted resources, and a skewed perception of a company’s outlook.

So, what is it that’s making your data dirty? What can a business or organization do to start addressing these concerns? Below is an excerpt from the eBook, where we have identified the five most common reasons why your data may be dirty. To read the full eBook, “The Clean Data Initiative,” download it here.

1 | Company Growth Through Acquisition

Your company has grown at a rapid pace through the acquisition of various companies. During this time, the systems and processes from the acquired companies were brought in as-is, with minimal integration except for some of the topline consolidated financial reporting.

This can be an effective way of rapidly acquiring companies and having them operate independently under a corporate umbrella. However, over time, each acquired business has its own data and own way of operating, leading to different processes and data.

When this happens, your company should refresh their data strategy and create a roadmap for the data they want to standardize and in what order.

2 | Highly Decentralized Organizations

Your company is operating in a highly decentralized manner and dislikes corporate overreach – especially related to processes and data. While the decentralized nature of operations allows your company to be nimble and entrepreneurial, it makes it difficult to establish enterprise data and process standards.

A change to your organization will often be driven by competitive pressure, regulatory and compliance requirements, and executive mandate. Working from the top down, your executive team needs to realize the importance of clean data, even if it effects the laissez-faire culture of your company.

3 | No One Knows Where or How to Start

The benefit of clean data seems apparent, but your company doesn’t know where to start. You kick off multiple initiatives to address specific data issues and challenges, but it feels like playing whack-a-mole. Every time you fix one problem, another problem seems to creep up somewhere else.

Understanding how Data Governance, Data Quality, and Master Data Management fit together is a starting requirement. The internet, blog posts, and case studies can provide a basic understanding of each topic, and eBook’s like “The Clean Data Initiative” can provide insight into the importance of each. Most importantly, work with someone that can guide you down the journey and help you understand how all the pieces fit together. A subject matter expert can help you figure out what solution is right for you.

4 | Data and Analytics Have Never Been a Priority

Unless forced to act, your company doesn’t see the need to take substantial action to clean their data. They are perfectly okay doing the minimum needed to keep business operations moving forward. They do not see data and analytics as a strategic differentiator.

This approach may work until the competition begins to offer more for less. At that point, your company will react, and by then the task to get to clean data is huge. You’ll need significant upfront investment on the foundational aspects, without realizing immediate benefit, which further compounds the issue.

When this happens, your company should assess the minimum level of effort to remain competitive and decide whether they wish to invest anything additionally to position themselves for future opportunities.

5 | Data is a Technology Responsibility­­­

While your technology organization manages the systems that contain data, your business views data as something that only the technology department needs to manage. Your business organization needs to be an equal stakeholder in managing data assets all the way from setting up the governance, getting access to, and using the data. Only through joint involvement can the necessary processes and standards be put in place across the company.

Data Quality Next Steps

Data quality is a big project to tackle, but the results of clean data are rewarding financially and operationally. Your company may be a victim of one of the mentioned issues, but how do you go about spreading the word or introducing the idea to decision makers? First, take some time to review our eBook, “The Clean Data Initiative,” a great starting point to help you fully understand what solution your company needs.

Need additional help? Reach out to a subject matter expert to discuss what your roadmap to improved data quality should look like.

Sense Corp is a digital and data consulting company that provides insights and solution to help your company with transformative projects and services. To learn more about ‘The Clean Data Initiative’ and the services we provide, visit our website.